Work Order Management: 12 KPIs Every FM Team Should Track

Work order KPIs tell an owner or an FM provider whether maintenance is being done on time, done right and done at a sensible cost. Choosing them is rarely the hard part. Defining them precisely enough that both sides of an FM contract get the same figure from the same data is. This guide covers 12 KPIs: the formula for each, how to read it, how it can be gamed, and what your system must capture for the number to be trusted.

Why Definitions Matter More Than the List

Most maintenance KPIs are simple ratios. The disputes come from the inputs. "Response" can mean a phone acknowledgement or a technician on site. "Completed" can mean made safe or permanently fixed. A P1 logged at 11pm may or may not be on the clock, depending on whether targets run 24/7 or in working hours.

Every facility management KPI below depends on the underlying work order record being complete and honest. That is the real job of a CAFM system or CMMS in performance management: capturing each lifecycle event as it happens, in records both parties can see.

Each step is a timestamp, and most of the 12 KPIs are calculated from the gaps between them.

The 12 Work Order KPIs at a Glance

Responsiveness KPIs

1. Mean time to respond (or acknowledge)

The average time from a work order being logged to the provider responding. The contract must say whether response means acknowledgement or attendance on site.

• Formula: Sum of (response timestamp − logged timestamp) ÷ work orders responded to, per priority.
• How to read it: Never report one blended average: fast responses to low-priority jobs hide slow P1s. Look at the slowest jobs as well as the mean, because those are what tenants remember.
• Failure mode or gaming risk: Tapping “acknowledge” in the app without anyone acting, or the helpdesk logging a phoned-in request late so the clock starts late.
• Data the CAFM must capture: A system-generated logging timestamp, priority set at creation, and a response event from the technician's mobile app, ideally backed by an asset QR scan.

2. Mean time to repair (MTTR)

The average time to fix a fault, measured from logging or from the start of work as agreed. It is the core speed measure for corrective work.

• Formula: Sum of (completion timestamp − start timestamp) ÷ completed corrective work orders.
• How to read it: Split it by priority, trade and asset class. A rising MTTR in one trade usually points to parts, skills or a particular subcontractor.
• Failure mode or gaming risk: Closing a job at the temporary fix and raising a new order for the permanent repair, or excluding “waiting for parts” time without an agreed rule. Read MTTR next to first-time fix and repeat rate.
• Data the CAFM must capture: Field completion timestamps, pause reasons (awaiting access, approval or parts) with start and stop times, and a make-safe status distinct from resolved.

3. SLA compliance %

The share of work orders that met their contracted response and resolution targets, usually the basis of the payment mechanism.

• Formula: Work orders meeting the SLA ÷ work orders due in the period × 100, per priority and per clock. For example, if 46 of 50 P2 jobs were resolved within target, P2 resolution compliance is 92%.
• How to read it: Report response and resolution separately: a provider can attend on time and still leave jobs open for weeks. Show breach counts too, since on low P1 volumes one miss moves the percentage sharply.
• Failure mode or gaming risk: Downgrading priority after logging so a late P2 becomes an on-time P3, or pausing the clock for reasons the contract does not recognise.
• Data the CAFM must capture: The priority matrix with targets per priority, working-hours calendars, an audit trail of every priority change, and only the pause reasons the contract allows.

Quality KPIs

4. First-time fix rate

The share of corrective jobs resolved on the first visit, with no return trip.

• Formula: Work orders completed in one visit ÷ total corrective work orders completed × 100.
• How to read it: A low first time fix rate usually means poor helpdesk diagnosis, the wrong trade dispatched or parts missing from the van.
• Failure mode or gaming risk: Recording the return visit as a brand-new work order, so the original appears to have been fixed first time.
• Data the CAFM must capture: Each attendance recorded against the work order, parent-child links for follow-ups, and a reason code when another visit is needed.

5. Repeat work order rate

The share of corrective jobs raised on the same asset for the same fault within a set window after a previous job was closed.

• Formula: Corrective work orders on the same asset and fault within N days of a previous closure ÷ total corrective work orders × 100.
• How to read it: Agree the window (for example 30 days) in advance. Clustered repeats on one asset call for root-cause analysis or a replacement decision, not only a performance conversation.
• Failure mode or gaming risk: Logging repeats against a different asset or a generic location, or free-text fault descriptions that cannot be matched.
• Data the CAFM must capture: A clean asset register with unique IDs (QR or barcode tags), structured fault codes and a closure date on every job.

6. Tenant satisfaction and reopened rate

Whether the requester agrees the job is done, tracked as a post-closure feedback score and the percentage of jobs reopened.

• Formula: Reopened work orders ÷ closed work orders × 100; satisfaction as the average rating, always shown with the response rate.
• How to read it: Reopened rate is harder to distort than a survey score because it does not depend on who answers. A score from a handful of responses tells you little.
• Failure mode or gaming risk: Requesting feedback only from happy tenants, closing without verification, or making tenants raise a new ticket instead of reopening.
• Data the CAFM must capture: The requester linked to each job, an automatic feedback request at closure, a reopen action that keeps the original ID, and a verification step.

Workload and Planning KPIs

7. Backlog size and backlog age

Open work that has not been completed, measured as a count, in labour hours and by age.

• Formula: Count of open work orders at period end; backlog in weeks = estimated open hours ÷ available labour hours per week; age = days since logging, in buckets such as 0–7, 8–30, 31–90 and 90+.
• How to read it: The trend matters more than the level. A steady backlog in weeks means capacity matches demand. A growing over-90-days bucket means work is being quietly abandoned.
• Failure mode or gaming risk: Bulk-cancelling old jobs before month end, or parking them in an “on hold” status excluded from the count.
• Data the CAFM must capture: Full status history, a mandatory cancellation reason and approver, estimated hours per job and technician availability.

8. PPM compliance rate

The share of scheduled planned preventive maintenance tasks completed within their tolerance window: the main test of whether the maintenance programme is being delivered.

• Formula: PPM tasks completed within tolerance ÷ PPM tasks due in the period × 100. For example, if 180 of 200 PPM tasks were completed on time, PPM compliance is 90%.
• How to read it: Define the tolerance. A widely used convention, set out in the Society for Maintenance & Reliability Professionals (SMRP) metrics, counts a task as compliant within 10% of its interval either side of the due date. Split by criticality: a missed fire pump test outweighs a missed filter clean.
• Failure mode or gaming risk: Ticking off checklists without doing the work, or moving due dates so tasks never become overdue.
• Data the CAFM must capture: A schedule generated from the asset register, original due dates that cannot be edited silently, and checklists with readings, photos, an asset scan and the technician's identity.

9. Schedule compliance

The share of all work planned for a week that was completed that week. Unlike PPM compliance, it includes planned corrective jobs and tests planning discipline.

• Formula: Scheduled work orders completed in the scheduled week ÷ work orders scheduled for that week × 100 (or in labour hours).
• How to read it: Low schedule compliance with high reactive volume means breakdowns keep displacing planned work, which usually shows up later as lower PPM compliance.
• Failure mode or gaming risk: Building the schedule after the week has ended, or scheduling only jobs that are certain to happen.
• Data the CAFM must capture: A snapshot of the weekly schedule frozen at the start of the week, plus scheduled and actual completion dates.

10. Planned vs reactive ratio

The share of maintenance effort that was planned (PPM and scheduled corrective work) rather than unplanned reactive work.

• Formula: Planned labour hours ÷ total maintenance labour hours × 100. Counts of work orders can be used, but hours are more reliable.
• How to read it: A rising planned share generally indicates more control. The usual rule of thumb is that planned work should dominate, but the right mix depends on building age, asset condition and contract scope, so set targets from your own baseline.
• Failure mode or gaming risk: Reclassifying reactive jobs as planned once scheduled, or counting orders when PPM routines are split into many small ones.
• Data the CAFM must capture: A work type set at creation and locked afterwards, and labour hours booked to each work order.

Productivity and Cost KPIs

11. Wrench time (technician utilisation)

The share of paid technician time spent on hands-on work rather than travel, waiting for access or permits, collecting parts and paperwork.

• Formula: Hands-on hours booked to work orders ÷ total paid technician hours × 100.
• How to read it: Most useful to FM providers managing labour cost. Low figures point to travel, parts availability or access delays. Use it to fix processes, not to rank technicians.
• Failure mode or gaming risk: Inflated hours booked to jobs. Formal wrench time studies use direct observation, so treat a CAFM-derived figure as a proxy.
• Data the CAFM must capture: Start and stop times per job from the mobile app, shift or attendance hours, and travel time recorded separately.

12. Work order cost per asset or per square foot

What maintenance costs, normalised so that assets, buildings and portfolios can be compared.

• Formula: Maintenance cost (labour, materials and subcontract) for the period ÷ assets in the class, or ÷ maintained area in square feet or metres.
• How to read it: Compare like with like: same asset class, similar building type and age, same cost boundary. Rising cost per asset shows when repairs are approaching the cost of replacement.
• Failure mode or gaming risk: Leaving costs out, such as subcontractor invoices or stock materials not linked to work orders. A low figure can also mean PPM is being skipped, so read it with PPM compliance.
• Data the CAFM must capture: Labour hours and rates, materials issued against each job, linked subcontract costs, the asset hierarchy and area per location.

Setting Targets Without Borrowed Benchmarks

Published benchmarks often come from manufacturing plants or markets with different contract models, asset ages and climates, so copied targets tend to be unachievable or meaningless. A more defensible approach:

• Fix data capture first. Until timestamps, priorities and asset links are consistent, any baseline is noise.
• Measure for at least three months, set a baseline per site, priority and trade, and set targets as improvements on it.
• Share the baseline with the other party when the KPI will be contracted, so the target is negotiated from evidence.

Building a KPI Dashboard: Owners vs FM Providers

The same work order data serves two audiences. An owner wants to know whether the building is looked after and the contract honoured. A provider wants to know where to act this week and whether the contract is profitable.

Owners with several buildings and contractors need cross-provider comparison, the core of multi-property owner reporting. Providers running many contracts need per-client KPI packs without manual consolidation, a recurring requirement for IFM providers. Comparing systems on this basis? Our guide to the best CAFM software in the UAE sets out what to test.

Why KPI Definitions Must Be Agreed in the Contract

In many UAE FM contracts, KPIs feed the payment mechanism: missed targets trigger deductions from the monthly fee, often capped. Every ambiguity in a definition then becomes a monthly negotiation. (Our SLA glossary entry explains how response and resolution targets, priorities and service credits fit together.)

For each contracted KPI, the contract or its KPI schedule should state:

• The exact formula, rounding and measurement period
• When each clock starts and stops, and whether it runs 24/7
• Permitted pauses and exclusions, such as denied access or client-caused delays
• The data source: which system and which record is authoritative
• Who may change priorities, timestamps or statuses, and how changes are audited
• How and when the client verifies completed work
• The deduction for each shortfall, any cap, and the deadline for agreeing the monthly result

That last point now has a tax dimension. Under the UAE e-invoicing framework an issued invoice cannot be edited, so a deduction agreed after invoicing becomes a credit note. As our guide to UAE e-invoicing for CAFM and CMMS explains, the answer is to agree the KPI result from system data before invoicing.

Define KPIs tightly and capture the evidence automatically: twelve well-defined work order KPIs tell you more than thirty loose ones. If you are still deciding what kind of system should hold that data, see CAFM vs CMMS vs IWMS.

Frequently Asked Questions